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          "html": "<html><body><table><thead><tr><td>Methods</td><td>R</td><td>P</td><td>F</td><td>FPS</td></tr></thead><tbody><tr><td>SegLink [26]</td><td>70.0</td><td>86.0</td><td>77.0</td><td>8.9</td></tr><tr><td> PixelLink [4]</td><td>73.2</td><td>83.0</td><td>77.8</td><td>:</td></tr><tr><td>TextSnake [13]</td><td>73.9</td><td>83.2</td><td>78.3</td><td>1.1</td></tr><tr><td>TextField [37]</td><td>75.9</td><td>87.4</td><td>81.3</td><td>5.2</td></tr><tr><td>MSR[38]</td><td>76.7</td><td>87.4</td><td>81.7</td><td>-</td></tr><tr><td>FTSN [3]</td><td>77.1</td><td>87.6</td><td>82.0</td><td>:</td></tr><tr><td>[LSE[30]</td><td>81.7</td><td>84.2</td><td>82.9</td><td>:</td></tr><tr><td>CRAFT [2]</td><td>78.2</td><td>88.2</td><td>82.9</td><td>8.6</td></tr><tr><td>MCN [16]</td><td>.79</td><td>.88</td><td>83</td><td>-</td></tr><tr><td>ATRR[35]</td><td>82.1</td><td>85.2</td><td>83.6</td><td>:</td></tr><tr><td>PAN[34]</td><td>83.8</td><td>84.4</td><td>84.1</td><td>30.2</td></tr><tr><td>DB[i2]</td><td>79.2</td><td>91.5.</td><td>84.9</td><td>32.0</td></tr><tr><td>DRRG [41]</td><td>82.30</td><td>88.05</td><td>85.08</td><td>-</td></tr><tr><td>Ours (SynText)</td><td>80.68</td><td>85.40</td><td>82.97</td><td>12.68</td></tr><tr><td>Ours (MLT-17)</td><td>84.54</td><td>86.62</td><td>85.57</td><td>12.31</td></tr></tbody></table></body></html>"
        },
        "img_idx": 0,
        "layout": "double"
      },
      {
        "type": "title",
        "bbox": [
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        "res": [
          {
            "text": "5. Conclusion",
            "confidence": 0.9989850521087646,
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        ],
        "img_idx": 0,
        "layout": "double"
      },
      {
        "type": "text",
        "bbox": [
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        "res": [
          {
            "text": "In this paper, we propose a novel adaptive bound-",
            "confidence": 0.9676509499549866,
            "text_region": [
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          },
          {
            "text": "ary proposal network for arbitrary shape text detection",
            "confidence": 0.9528875350952148,
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            ]
          },
          {
            "text": "which adopt an boundary proposal model to generate coarse",
            "confidence": 0.9852272272109985,
            "text_region": [
              [
                444,
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              ],
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              ],
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              ]
            ]
          },
          {
            "text": "boundary proposals, and then adopt an adaptive boundary",
            "confidence": 0.9945465922355652,
            "text_region": [
              [
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              [
                837,
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              ],
              [
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              ],
              [
                444,
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              ]
            ]
          },
          {
            "text": "deformation model combined with GCN and RNN to per-",
            "confidence": 0.9793977737426758,
            "text_region": [
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              [
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          }
        ],
        "img_idx": 0,
        "layout": "double"
      }
    ]
  }

export default example;